Scenario

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## irace scenario:
scenarioFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/scenario.txt"
execDir = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace"
parameterFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/parameters.txt"
forbiddenExps = list(<bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>,     <bytecode>, <bytecode>, <bytecode>, <bytecode>, <bytecode>) = expression(neuroniosDensos1%%2 != 0, neuroniosDensos2%%2 != 0, (maxpooling1 + maxpooling2 + maxpooling3 + maxpooling4 + maxpooling5 + maxpooling6 + maxpooling7 + maxpooling8) > 4, tamanhoFiltros2%%2 == 0, tamanhoFiltros3%%2 == 0, tamanhoFiltros4%%2 == 0, tamanhoFiltros5%%2 == 0, tamanhoFiltros6%%2 == 0, tamanhoFiltros7%%2 == 0, tamanhoFiltros8%%2 == 0)
forbiddenFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/forbidden.txt"
initConfigurations = NULL
configurationsFile = ""
logFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/irace.Rdata"
recoveryFile = ""
instances = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")
trainInstancesDir = ""
trainInstancesFile = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/train-instances.txt"
sampleInstances = FALSE
testInstancesDir = ""
testInstancesFile = ""
testInstances = NULL
testNbElites = 1
testIterationElites = FALSE
testType = "t.none"
firstTest = 2
eachTest = 1
targetRunner = "D:/Users/SuperUser/OneDrive/mestrado/pesquisa/irace/cifar10-irace - exp7/irace/target-runner.bat"
targetRunnerLauncher = ""
targetRunnerLauncherArgs = "{targetRunner} {targetRunnerArgs}"
targetRunnerRetries = 5
targetRunnerData = ""
targetRunnerParallel = NULL
targetEvaluator = NULL
deterministic = TRUE
maxExperiments = 1000
maxTime = 0
budgetEstimation = 0.02
minMeasurableTime = 0.01
parallel = 2
loadBalancing = TRUE
mpi = FALSE
batchmode = "0"
digits = 2
quiet = FALSE
debugLevel = 0
seed = 123456
softRestart = TRUE
softRestartThreshold = 0.01
elitist = TRUE
elitistNewInstances = 1
elitistLimit = 2
repairConfiguration = NULL
capping = FALSE
cappingType = "median"
boundType = "candidate"
boundMax = NULL
boundDigits = 0
boundPar = 1
boundAsTimeout = TRUE
postselection = 0
aclib = FALSE
nbIterations = 0
nbExperimentsPerIteration = 0
minNbSurvival = 0
nbConfigurations = 0
mu = 5
confidence = 0.95
## end of irace scenario

Parameters

n_total n_fixed n_int n_real n_cat n_ord n_conditional n_dependent
38 0 37 1 0 0 30 0

Parameters tree

 
├─camadasConvolucionais
│ ├─maxpooling2
│ ├─maxpooling3
│ ├─maxpooling4
│ ├─maxpooling5
│ ├─maxpooling6
│ ├─maxpooling7
│ ├─maxpooling8
│ ├─batchNormalization2
│ ├─batchNormalization3
│ ├─batchNormalization4
│ ├─batchNormalization5
│ ├─batchNormalization6
│ ├─batchNormalization7
│ ├─batchNormalization8
│ ├─numFiltrosInd2
│ ├─numFiltrosInd3
│ ├─numFiltrosInd4
│ ├─numFiltrosInd5
│ ├─numFiltrosInd6
│ ├─numFiltrosInd7
│ ├─numFiltrosInd8
│ ├─tamanhoFiltros2
│ ├─tamanhoFiltros3
│ ├─tamanhoFiltros4
│ ├─tamanhoFiltros5
│ ├─tamanhoFiltros6
│ ├─tamanhoFiltros7
│ └─tamanhoFiltros8
├─maxpooling1
├─batchNormalization1
├─camadasDensas
│ ├─neuroniosDensos1
│ └─neuroniosDensos2
├─dropout
├─learningIndex
├─batchIndex
└─numEpocas

Parameters file

Click to show
camadasConvolucionais "--nc="  i (1,8)          
maxpooling1           "--mp1=" i (0,1)          
maxpooling2           "--mp2=" i (0,1)           | camadasConvolucionais > 1
maxpooling3           "--mp3=" i (0,1)           | camadasConvolucionais > 2
maxpooling4           "--mp4=" i (0,1)           | camadasConvolucionais > 3
maxpooling5           "--mp5=" i (0,1)           | camadasConvolucionais > 4
maxpooling6           "--mp6=" i (0,1)           | camadasConvolucionais > 5
maxpooling7           "--mp7=" i (0,1)           | camadasConvolucionais > 6
maxpooling8           "--mp8=" i (0,1)           | camadasConvolucionais > 7
batchNormalization1   "--bn1=" i (0,1)          
batchNormalization2   "--bn2=" i (0,1)           | camadasConvolucionais > 1
batchNormalization3   "--bn3=" i (0,1)           | camadasConvolucionais > 2
batchNormalization4   "--bn4=" i (0,1)           | camadasConvolucionais > 3
batchNormalization5   "--bn5=" i (0,1)           | camadasConvolucionais > 4
batchNormalization6   "--bn6=" i (0,1)           | camadasConvolucionais > 5
batchNormalization7   "--bn7=" i (0,1)           | camadasConvolucionais > 6
batchNormalization8   "--bn8=" i (0,1)           | camadasConvolucionais > 7
numFiltrosInd2        "--nf2=" i (5,8)           | camadasConvolucionais > 1
numFiltrosInd3        "--nf3=" i (5,8)           | camadasConvolucionais > 2
numFiltrosInd4        "--nf4=" i (5,8)           | camadasConvolucionais > 3
numFiltrosInd5        "--nf5=" i (5,8)           | camadasConvolucionais > 4
numFiltrosInd6        "--nf6=" i (5,8)           | camadasConvolucionais > 5
numFiltrosInd7        "--nf7=" i (5,8)           | camadasConvolucionais > 6
numFiltrosInd8        "--nf8=" i (5,8)           | camadasConvolucionais > 7
tamanhoFiltros2       "--tf2=" i (3,11)          | camadasConvolucionais > 1
tamanhoFiltros3       "--tf3=" i (3,11)          | camadasConvolucionais > 2
tamanhoFiltros4       "--tf4=" i (3,11)          | camadasConvolucionais > 3
tamanhoFiltros5       "--tf5=" i (3,11)          | camadasConvolucionais > 4
tamanhoFiltros6       "--tf6=" i (3,11)          | camadasConvolucionais > 5
tamanhoFiltros7       "--tf7=" i (3,11)          | camadasConvolucionais > 6
tamanhoFiltros8       "--tf8=" i (3,11)          | camadasConvolucionais > 7
camadasDensas         "--nd="  i (1,3)          
neuroniosDensos1      "--nd1=" i (4,128)         | camadasDensas > 1
neuroniosDensos2      "--nd2=" i (4,128)         | camadasDensas > 2
dropout               "--dr="  r (0,0.5)        
learningIndex         "--li="  i (0,5)          
batchIndex            "--bti=" i (4,10)         
numEpocas             "--ne="  i (10,300)       

General information

  • irace version: 3.5.6863679
  • Iterations: 20
  • Configurations: 466
  • Instances: 10
  • Experiments: 953
  • Elite configurations: 4
  • Soft restarts: 0
  • Rejected configurations: 0
  • Running time (seconds): 23 (CPU-user); 32 (CPU-sys); 367444 (Wall-clock)
  • Termination reason: Not enough budget to race more than the minimum configurations

By iteration

By instance

Elite configurations

The final best configurations found by irace are:

Parallel coordinates visualization (only elites)

#> Warning in min(x): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(data[, ".FITNESS."]): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(data[, ".FITNESS."]): nenhum argumento não faltante para max; retornando -Inf

Sampling model

The frequency of the parameter values sampled by irace:

#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning in min(x, na.rm = na.rm): nenhum argumento não faltante para min; retornando Inf
#> Warning in max(x, na.rm = na.rm): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf
#> Warning: Groups with fewer than two data points have been dropped.
#> Warning in max(ids, na.rm = TRUE): nenhum argumento não faltante para max; retornando -Inf

Testing performance

  • Number of elites tested: 1
  • Iteration elites tested: FALSE

Performance of the elite configurations on the test instances

#> No test instances given.

Final elite configurations on the test instances

#> No test instances given.

Iteration elite configurations on the test instances

#> Iteration elites were not tested.

Training performance

Performance of the final elite configurations on the training instances

Final elite configurations on the training instances

Races overview

Convergence plot

This is a simplified version of the visualization you can obtain with acviz.

Disabled because sections$convergence is FALSE.


Report generated by iraceplot version 1.3.